Communication resources such as radio frequency channels are, at least at the present time, limited in quantity. Notwithstanding this limitation, communication needs continue to rapidly increase. Dispatch, selective call, and cellular communications, to name a few, are all being utilized by an increasing number of users. Without appropriate technological advances, many users will face either impaired service or possibly a complete lack of available service.
One recent technological advance intended to increase the efficiency of data throughput, and hence decrease system capacity needs to thereby allow more communications to be supported by the available limited resources, is speech coding. Code Excited Linear Prediction (CELP) speech coders and Vector Sum Excited Linear Prediction (VSELP) speech coders (the latter being a class of CELP coders) have been proposed that exhibit good performance at relatively low data rates. Rather than transmitting the original voice information itself, or a digitized version thereof, such speech coders utilize linear prediction techniques to allow a coded representation of the voice information to be transmitted instead. Utilizing the coded representation upon receipt, the voice message can then be reconstructed. For a general description of one version of a CELP approach, see U.S. Pat. No. 4,933,957 to Bottau et al., which describes a low bit rate voice coding method and system.
CELP type speech coders derive an excitation signal by summing a long term prediction vector with one or more codebook vectors, with each vector being scaled by an appropriate gain prior to summing. A linear predictive filter receives the resultant excitation vector and introduces spectral shaping to produce a resultant synthetic speech. Properly configured, the synthetic speech provided by such a speech coder will realistically mimic the original voice message.
As just mentioned, the excitation vectors are scaled by an appropriate gain prior to summing. These gains are typically originally calculated at the time of coding the speech, and are then transmitted to the receiver that will synthesize the speech as described above. Various methods of gain quantization prior to such transmission are used in the art, including scalar quantization and vector quantization (the latter being more efficient). The bits used to code this gain information are sensitive to bit errors. If the gain values are decoded incorrectly due to channel errors, the error, in addition to detrimentally affecting the current subframe's excitation, will propagate forward in time as well since the corrupted excitation vector will also be fed into the long term prediction state for later use in developing subsequent long term prediction vectors.
One helpful method for quantizing such gains for low data rate speech coders is described in the article "Vector Sum Excited Linear Prediction (VSELP) Speech Coding at 8KBPS," by Ira Gerson and Mark Jasiuk, which article appears in The Proceedings of the International Conference On Acoustics, Speech and Signal Processing, at pages 461-464, as published in April of 1990 (the contents of which are incorporated herein by this reference).
Notwithstanding the improvements offered by the teachings in the above reference, a method to more efficiently code the gain values, while simultaneously reducing the sensitivity of the gain bits to errors, is needed. This need is driven by three particular demands. First, there is a continued need to reduce speech coder data rates. Second, there is a need to maintain (or improve) good speech quality. Third, there is a need to design in robustness to channel errors. These three requirements are often critical to success in speech coder applications.